Appraisal of active tectonics using DEM-based hypsometric integral and trend surface analysis in Emilia-Romagna Apennines, northern Italy

Abstract

The hypsometric integral (HI) has generally been used to explain the stages of landscape evolution and erosional processes. It is an important tool to investigate tectonics and lithologic and climatic effects on topographic change. We analyzed the significance of the HI to investigate active tectonics in the Emilia-Romagna Apennines of northern Italy. We used a digital elevation model of 5-m spatial resolution to calculate grid-based HI values. The HI distribution does not show clear spatial patterns of high and low HI values. However, when statistical methods of local indices of spatial autocorrelation were applied, it was possible to identify clear clusters of high and low HI values. Trend surface analysis (TSA) was carried out to distinguish areas with anomalously high and low elevations, and to observe their spatial correlation with the HI and regional geological structures. The results indicate that the high HI values and TSA anomalies are positively correlated with the areas of high tectonic activity and along the regional tectonic structures

Geomorphic analysis of transient landscapes in the Sierra Madre de Chiapas and Maya Mountains (northern Central America): implications for the North American–Caribbean–Cocos plate boundary

“…This index proved to be efficient in evaluating the response of landscapes to active tectonics (e.g., Pérez-Peña et al, 2009;Mahmood and Gloaguen, 2012;Siddiqui and Soldati, 2014;Andreani et al, 2014;Domínguez-González et al, 2015). According to Pike and Wilson (1971), the HI for a given area can be approximated with Eq.…”

Morphometric evaluation of the Afşin-Elbistan lignite basin using kernel density estimation and Getis-Ord’s statistics of DEM derived indices, SE Turkey

“…Sarp and Duzgun (2012) analyzed the spatial randomness of morphometric indices (Vf, asymmetry factor (Af), and SL) in the Bolu pull-apart basin area by using the weighted correlation coefficient Moran's I. Siddiqui and Soldati (2014) analyzed the spatial autocorrelation of the HI in the Emilia-Romagna Apennines, northern Italy to identify the clusters of high and low HI values.…”

Active tectonic deformation along rejuvenated faults in tropical Borneo: Inferences obtained from tectono-geomorphic evaluation

“…Spatial autocorrelation measures the degree of sameness of spatially distributed values of a single variable within their neighborhood (Moran, 1950;Cliff and Ord, 1981;Ratcliffe and McCullagh, 1998;Pérez-Peña et al, 2009a;Siddiqui and Soldati, 2014). We used Moran's I (Moran, 1950) which is regarded as the best known measure to test for spatial autocorrelation (Pérez-Peña et al, 2009a).…”